- The document discusses implementing enterprise search and compares Google Search to alternative options. It covers topics like how search engines work, the architecture of Google Search, and top 5 requirements for enterprise search implementation.
- For each requirement, it identifies disadvantages of using Google Search and discusses alternative implementation options that may perform better like Apache Solr, Endeca, and Autonomy.
- The overall conclusion is that no single search engine fulfills all enterprise needs, and custom application development is often required to fully meet requirements, allowing the use of various tools.
Building Search Systems for the EnterpriseYunyao Li
This is a nice high-level summary for Gumshoe, the enterprise engine built by our group, which is currently powering IBM intranet search. One of SIGIR 2011 Industrial Track Keynote Talk.
Enterprise Search in the Big Data Era: Recent Developments and Open ChallengesYunyao Li
This is the slides used in our 3-hour tutorial at VLDB'2014.
Yunyao Li, Ziyang Liu, Huaiyu Zhu: Enterprise Search in the Big Data Era: Recent Developments and Open Challenges. PVLDB 7(13): 1717-1718 (2014)
Abstract:
Enterprise search allows users in an enterprise to retrieve desired information through a simple search interface. It is widely viewed as an important productivity tool within an enterprise. While Internet search engines have been highly successful, enterprise search remains notoriously challenging due to a variety of unique challenges, and is being made more so by the increasing heterogeneity and volume of enterprise data. On the other hand, enterprise
search also presents opportunities to succeed in ways beyond current Internet search capabilities. This tutorial presents an organized overview of these challenges and opportunities, and reviews the state-of-the-art techniques for building a reliable and high quality enterprise search engine, in the context of the rise of big data.
Presented at SQL Saturday Atlanta May 18, 2013
Text mining is projected to dominate data mining, and the reasons are evident: we have more text available than numeric data. Microsoft introduced a new technology to SQL Server 2012 called Semantic Search. This session's detailed description and demos give you important information for the enterprise implementation of Tag Index and Document Similarity Index. The demos include a web-based Silverlight application, and content documents from Wikipedia. We'll also look at strategy tips for how to best leverage the new semantic technology with existing Microsoft data mining.
Text mining is projected to dominate data mining, and the reasons are evident: we have more text available than numeric data. Microsoft introduced a new technology to SQL Server 2012 called Semantic Search. This session's detailed description and demos give you important information for the enterprise implementation of Tag Index and Document Similarity Index. The demos include a web-based Silverlight application, and content documents from Wikipedia. We'll also look at strategy tips for how to best leverage the new semantic technology with existing Microsoft data mining.
Speaker: Philippe Mizrahi - Associate Product Manager - Lyft
Abstract: Philippe Mizrahi works on Lyft’s data discovery and metadata engine, Amundsen. With the help of a Neo4j graph database, Amundsen has improved Lyft’s data discovery by reducing time to discover data by 10x.
During this session, Philippe will dive deep into Amundsen’s use cases, impact, and architecture, which effectively combines a comprehensive knowledge graph based upon Neo4j, centralized metadata and other search ranking optimizations to discover data quickly.
Building Search Systems for the EnterpriseYunyao Li
This is a nice high-level summary for Gumshoe, the enterprise engine built by our group, which is currently powering IBM intranet search. One of SIGIR 2011 Industrial Track Keynote Talk.
Enterprise Search in the Big Data Era: Recent Developments and Open ChallengesYunyao Li
This is the slides used in our 3-hour tutorial at VLDB'2014.
Yunyao Li, Ziyang Liu, Huaiyu Zhu: Enterprise Search in the Big Data Era: Recent Developments and Open Challenges. PVLDB 7(13): 1717-1718 (2014)
Abstract:
Enterprise search allows users in an enterprise to retrieve desired information through a simple search interface. It is widely viewed as an important productivity tool within an enterprise. While Internet search engines have been highly successful, enterprise search remains notoriously challenging due to a variety of unique challenges, and is being made more so by the increasing heterogeneity and volume of enterprise data. On the other hand, enterprise
search also presents opportunities to succeed in ways beyond current Internet search capabilities. This tutorial presents an organized overview of these challenges and opportunities, and reviews the state-of-the-art techniques for building a reliable and high quality enterprise search engine, in the context of the rise of big data.
Presented at SQL Saturday Atlanta May 18, 2013
Text mining is projected to dominate data mining, and the reasons are evident: we have more text available than numeric data. Microsoft introduced a new technology to SQL Server 2012 called Semantic Search. This session's detailed description and demos give you important information for the enterprise implementation of Tag Index and Document Similarity Index. The demos include a web-based Silverlight application, and content documents from Wikipedia. We'll also look at strategy tips for how to best leverage the new semantic technology with existing Microsoft data mining.
Text mining is projected to dominate data mining, and the reasons are evident: we have more text available than numeric data. Microsoft introduced a new technology to SQL Server 2012 called Semantic Search. This session's detailed description and demos give you important information for the enterprise implementation of Tag Index and Document Similarity Index. The demos include a web-based Silverlight application, and content documents from Wikipedia. We'll also look at strategy tips for how to best leverage the new semantic technology with existing Microsoft data mining.
Speaker: Philippe Mizrahi - Associate Product Manager - Lyft
Abstract: Philippe Mizrahi works on Lyft’s data discovery and metadata engine, Amundsen. With the help of a Neo4j graph database, Amundsen has improved Lyft’s data discovery by reducing time to discover data by 10x.
During this session, Philippe will dive deep into Amundsen’s use cases, impact, and architecture, which effectively combines a comprehensive knowledge graph based upon Neo4j, centralized metadata and other search ranking optimizations to discover data quickly.
Video: https://www.youtube.com/watch?v=Rt2oHibJT4k
Technologies such as Hadoop have addressed the "Volume" problem of Big Data, and technologies such as Spark have recently addressed the "Velocity" problem – but the "Variety" problem is largely unaddressed – there is a lot of manual "data wrangling" to mange data models.
These manual processes do not scale well. Not only is the variety of data increasing, also the rate of change in the data definitions is increasing. We can’t keep up. NoSQL data repositories can handle storage, but we need effective models of the data to fully utilize it.
This talk will present tools and a methodology to manage Big Data Models in a rapidly changing world. This talk covers:
Creating Semantic Metadata Models of Big Data Resources
Graphical UI Tools for Big Data Models
Tools to synchronize Big Data Models and Application Code
Using NoSQL Databases, such as Amazon DynamoDB, with Big Data Models
Using Big Data Models with Hadoop, Storm, Spark, Giraph, and Inference
Using Big Data Models with Machine Learning to generate Predictive Models
Developer Collaborative/Coordination processes using Big Data Models and Git
Managing change – Big Data Models with rapidly changing Data Resources
MongoDB Certification Study Group - May 2016Norberto Leite
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB
Democratizing Data within your organization - Data DiscoveryMark Grover
n this talk, we talk about the challenges at scale in an organization like Lyft. We delve into data discovery as a challenge towards democratizing data within your organization. And, go in detail about the solution to solve the challenge of data discovery.
How to build your own Delve: combining machine learning, big data and SharePointJoris Poelmans
You are experiencing the benefits of machine learning everyday through product recommendations on Amazon & Bol.com, credit card fraud prevention, etc… So how can we leverage machine learning together with SharePoint and Yammer. We will first look into the fundamentals of machine learning and big data solutions and next we will explore how we can combine tools such as Windows Azure HDInsight, R, Azure Machine Learning to extend and support collaboration and content management scenarios within your organization.
Engineering patterns for implementing data science models on big data platformsHisham Arafat
Discussion of practically implementing data science models on big data platforms from engineering perspective. An eye opener on the engineering factors associated with designing and working solution. We use a simple text mining example on social media analytics for brand marketing. At the first while, it seems simple solution however if you go deeply and think on implementation aspects of even a simple analytics model, you can discover the degree of complexity at each part of the solution. An Abstraction of the Big Data key advantages would be very helpful to select appropriate Big Data technology components out of very large landscape. Two examples with reference are given for using Lambda Architecture and unusual way of image processing using Big Data abstraction provided.
PatSeer Patent Database brings you a fresh Web 2.0 approach to searching, analyzing, comparing, collaborating, sharing and managing patent data projects. It’s simple, smart and serious enough to meet the needs of most demanding professional searchers too. PatSeer includes full text of 15 countries and Biblio data of 95+ countries to ensure that your patent search is comprehensive and reliable.
PatSeer can offer a multi-dimensional solution for the entire company’s patent project requirements:
- It creates a centralized work environment for your internal team to manage and work on patent data projects, carry out analysis and deliver insights
- It can be configured to share access to various projects with members across departments within the company that may need the insights or collaborate on a project
- It can be used to assign projects to external service providers for analysis, litigation analysis or other work while managing control, access and security at every level
- It can be used to urgently pull up, filter and analyze patents for quick insights needed to make immediate decisions from any location, meeting room or device with web access
- It creates a unified patent project management environment integrating all the various resources, functions and people involved in the process eliminating the inefficiencies and challenges usually faced by those who rely on and work with patent projects and data.
PatSeer provides a multiple advantage for service providers:
- It creates a centralized work environment for your team to manage and work on patent data projects, carry out analysis and deliver insights. Managers can assign projects to research associates and monitor progress.
- It doubles as a web based delivery platform for customers giving them a richer engaging experience than Excel, while helping you manage the quality of your deliverables
A wide range of permission settings give you complete control of what to make visible or editable to your customer and also allow you to engage other stakeholders of the project such as external counsel or senior management
- Reduced risk of failure – As compared to developing and maintaining inhouse platforms, with PatSeer, you are using a platform thats been developed with tried and tested practices and where continued product innovation ensures the platform meets markets needs today and in the future.
Both PatSeer Projects and PatSeer Premier have been architecturally designed keeping in mind the most critical needs of service providers while understanding each one can have their own unique requirements.
PatSeer Premier (as well as PatSeer Projects) offers a quick “sign in & get started” solution ready to use in minutes while extending extensive administrative controls that allow you to set up a work environment for patent projects as well as a collaborative online sharing delivery platform for your customers on your own terms, based on your specific requirements.
Enterprise Search in Practice: A Presentation of Survey Results and Areas for...Findwise
The presentation has two main focuses. First, to present some interesting and sometimes rather contradicting findings from the Enterprise Search and Findability survey 2012. Second, to introduce an holistic approach to implementing search technology involving five different aspects that are all important to succeed and to reach findability rather than just the ability to search.
Presented at Gilbane Conference 2012 in Boston USA on the 28th of November by Mattias Ellison.
Video: https://www.youtube.com/watch?v=Rt2oHibJT4k
Technologies such as Hadoop have addressed the "Volume" problem of Big Data, and technologies such as Spark have recently addressed the "Velocity" problem – but the "Variety" problem is largely unaddressed – there is a lot of manual "data wrangling" to mange data models.
These manual processes do not scale well. Not only is the variety of data increasing, also the rate of change in the data definitions is increasing. We can’t keep up. NoSQL data repositories can handle storage, but we need effective models of the data to fully utilize it.
This talk will present tools and a methodology to manage Big Data Models in a rapidly changing world. This talk covers:
Creating Semantic Metadata Models of Big Data Resources
Graphical UI Tools for Big Data Models
Tools to synchronize Big Data Models and Application Code
Using NoSQL Databases, such as Amazon DynamoDB, with Big Data Models
Using Big Data Models with Hadoop, Storm, Spark, Giraph, and Inference
Using Big Data Models with Machine Learning to generate Predictive Models
Developer Collaborative/Coordination processes using Big Data Models and Git
Managing change – Big Data Models with rapidly changing Data Resources
MongoDB Certification Study Group - May 2016Norberto Leite
Study group session to review the certification exam regarding material covered, exam structure and technical requirements. DBA and Developers track covered to ensure the technical expertise of individuals on subject matter topics specific to MongoDB
Democratizing Data within your organization - Data DiscoveryMark Grover
n this talk, we talk about the challenges at scale in an organization like Lyft. We delve into data discovery as a challenge towards democratizing data within your organization. And, go in detail about the solution to solve the challenge of data discovery.
How to build your own Delve: combining machine learning, big data and SharePointJoris Poelmans
You are experiencing the benefits of machine learning everyday through product recommendations on Amazon & Bol.com, credit card fraud prevention, etc… So how can we leverage machine learning together with SharePoint and Yammer. We will first look into the fundamentals of machine learning and big data solutions and next we will explore how we can combine tools such as Windows Azure HDInsight, R, Azure Machine Learning to extend and support collaboration and content management scenarios within your organization.
Engineering patterns for implementing data science models on big data platformsHisham Arafat
Discussion of practically implementing data science models on big data platforms from engineering perspective. An eye opener on the engineering factors associated with designing and working solution. We use a simple text mining example on social media analytics for brand marketing. At the first while, it seems simple solution however if you go deeply and think on implementation aspects of even a simple analytics model, you can discover the degree of complexity at each part of the solution. An Abstraction of the Big Data key advantages would be very helpful to select appropriate Big Data technology components out of very large landscape. Two examples with reference are given for using Lambda Architecture and unusual way of image processing using Big Data abstraction provided.
PatSeer Patent Database brings you a fresh Web 2.0 approach to searching, analyzing, comparing, collaborating, sharing and managing patent data projects. It’s simple, smart and serious enough to meet the needs of most demanding professional searchers too. PatSeer includes full text of 15 countries and Biblio data of 95+ countries to ensure that your patent search is comprehensive and reliable.
PatSeer can offer a multi-dimensional solution for the entire company’s patent project requirements:
- It creates a centralized work environment for your internal team to manage and work on patent data projects, carry out analysis and deliver insights
- It can be configured to share access to various projects with members across departments within the company that may need the insights or collaborate on a project
- It can be used to assign projects to external service providers for analysis, litigation analysis or other work while managing control, access and security at every level
- It can be used to urgently pull up, filter and analyze patents for quick insights needed to make immediate decisions from any location, meeting room or device with web access
- It creates a unified patent project management environment integrating all the various resources, functions and people involved in the process eliminating the inefficiencies and challenges usually faced by those who rely on and work with patent projects and data.
PatSeer provides a multiple advantage for service providers:
- It creates a centralized work environment for your team to manage and work on patent data projects, carry out analysis and deliver insights. Managers can assign projects to research associates and monitor progress.
- It doubles as a web based delivery platform for customers giving them a richer engaging experience than Excel, while helping you manage the quality of your deliverables
A wide range of permission settings give you complete control of what to make visible or editable to your customer and also allow you to engage other stakeholders of the project such as external counsel or senior management
- Reduced risk of failure – As compared to developing and maintaining inhouse platforms, with PatSeer, you are using a platform thats been developed with tried and tested practices and where continued product innovation ensures the platform meets markets needs today and in the future.
Both PatSeer Projects and PatSeer Premier have been architecturally designed keeping in mind the most critical needs of service providers while understanding each one can have their own unique requirements.
PatSeer Premier (as well as PatSeer Projects) offers a quick “sign in & get started” solution ready to use in minutes while extending extensive administrative controls that allow you to set up a work environment for patent projects as well as a collaborative online sharing delivery platform for your customers on your own terms, based on your specific requirements.
Enterprise Search in Practice: A Presentation of Survey Results and Areas for...Findwise
The presentation has two main focuses. First, to present some interesting and sometimes rather contradicting findings from the Enterprise Search and Findability survey 2012. Second, to introduce an holistic approach to implementing search technology involving five different aspects that are all important to succeed and to reach findability rather than just the ability to search.
Presented at Gilbane Conference 2012 in Boston USA on the 28th of November by Mattias Ellison.
Tips and tricks for getting the best out of solr on windows azurelucenerevolution
Presented by Brian Benz, Senior Technical Evangelist, Microsoft Open Technologies, Inc.
This session will cover tips and tricks for getting the most out of Solr in Windows Azure. Windows Azure enables quick and easy installation and setup of Solr search functionality in a variety of ways, and lets you focus on managing and operating Solr servers in our managed environment. We’ll cover multiple options for setting up Solr in Windows Azure, including working examples.
Got a bit obsessed with the World Cup! And trying to marry my work as Strategist and my love for the beautiful game! So please indulge me. Here's a look at how brands are celebrating the World Cup.
This presentation provides a short overview in photos of local Kenyans and how they manually extract gold from the surface soils. All photos were taken on mining concessions owned by Stockport. Local mining activity on Stockport concessions is not endorsed by Stockport, and does not reflect company health or safety standards.
This is a presentation on E-Commerce and its practices. It was deliberately made with self-explanatory slides in order to save the time of the readers! Minimum reading and maximum knowledge is what i believe in ! how ever this is my first ever ppt. More to come
Site search is one of the core functionality of any website. This talk provides an overview of internal workings of CQ5 search, its limitations for implementing site search functionality and discusses design patterns & challenges for integrating various 3rd party search providers with CQ5/AEM.
13 Things Developers Forget When Launching Public WebsitesAJi
This presentation will describe 13 tools developers typically forget when launching a public facing websites based on best practices in SEO and audience building. These are the tools both marketing and IT teams can use, or the savvy business owner can embrace, to help set yourself up for success.
The presentation was originally presented at the Kansas City Developers Conference in June of 2015
Planning Your Migration to SharePoint Online #SPBiz60Christian Buckley
Session from SPBiz.com online event on June 18th, 2015. It’s always best to begin with a plan, and this session will provide a framework for developing your own migration plan. While tools will help automate some aspects of the content move, much of the complexity of a SharePoint migration happens before a tool is installed. This session will help analysts, project managers and admin of SharePoint to reduce migration time and increase success.
The Enterprise Content Management features in SharePoint have steadily improved with each new release of the platform. In this session, we will explore the top 10 new ECM features that have been added to SharePoint 2013, with an emphasis on "new". The session will include demos that showcase real-world examples of how each feature can be used to enhance the overall user experience when working with email, collaborative documents as well as official records.
SEO is tremendously important in the Internet attention competition. Not all websites use their potential to appear amongst the top search results. SEO needs to be considered from the very beginning of the project. There are some architectural principles to follow. Furthermore many optimizations should be done along the way. Last year we have founded our sister company Amazee Metrics which focuses on SEO, SEM, Web Analytics and Online Marketing. We are working together hand in hand to increase our client's reach and conversions. I will give hands on tipps for Drupal as well as practical advice for those who manage stakeholders.
Having content that is technically optimized to appear on all platforms and provide quick, stable and successful user experiences is more important than ever. This presentation provides an easy to understand explanation of how to avoid, find and fix technical seo mistakes.
Decision CAMP 2014 - Erik Marutian - Using rules-based gui framework to power...Decision CAMP
In this presentation we will describe our experience developing with a highly dynamic web application for a large bank using rules-based technology. We needed to:
build new as well as to enhance existing systems to comply with customer due diligence
apply a business rules management system to present a complex user interaction logic and to dynamically control completeness of a complex client onboarding process spread out through multiple systems and channels.
We selected OpenRules Dialog to be used as a general purpose rule engine as well as to replace graphical components (a survey type dynamic web based application) behind one of the channels.
By replacing one of the original components with the OpenRules GUI Framework, we were able to:
Dramatically reduce components cost and schedule:
The cost in our specific example was reduced by a factor of 10
The schedule, at the same time, was also reduced from 6 months to 2 months
Improve overall user experience:
Flexibility of the framework allowed meeting all specific business UX requirements. Even those that the original component could not meet.
Simplify maintenance and escape vendor “lock in”:
The “open source” nature meant that we owned all pieces of the framework at any time.
In additional, the framework allowed developing all requirements with minimal customization to the core features.
We will demo our web application with explanations how quite complex presentation and interaction logic was implemented using intuitive, business-oriented decision tables in MS Excel.
Atlan Product Metering Case Challenge Summary:
The document outlines the importance of metering a SaaS product, specifically for SaaS B2B products. It highlights the benefits of accurate usage tracking, fair billing, resource optimization, cost control, upselling opportunities, and competitive differentiation. The goal is to align pricing with customers' ROI, optimize internal resources, and provide cost and usage visibility patterns.
The tasks for the product manager include researching different SaaS tools, capturing how metering is implemented in at least three tools, and defining the metrics and usage parameters for product metering. The proposed approach should be simple to implement and easy for both internal teams and customers to understand.
The desired outcomes are to create a flexible metering framework that accommodates various pricing models and billing structures and to provide a recommendation in the form of a document.
The document also includes a table of contents with sections discussing the need for data catalog software, the users of data catalog software in a company, capturing product metrics, factors driving data catalog pricing, and specific pricing details of Alation, castorDoc, Google Cloud Data Catalog, and Atlan.
The solution section presents two recommended pricing solutions for Atlan: a simple and transparent pricing model and a usage-based pricing model. The document concludes with a thank you note.
Overall, the document provides a comprehensive overview of the Atlan Product Metering Case Challenge, covering various aspects related to SaaS product metering and pricing.
The slides describe the 10 most important On Page SEO elements which every web development company shall address, if it is to get top ranks in search engines.
How Agile Technical SEO Can Add Value To Your SEO Campaign, by Adam GentBranded3
Google is constantly evolving and a webmaster’s ability to react to changes is key to any successful SEO campaign. However, what happens when you can’t get technical SEO recommendations over the line? This slideshow focuses on how you can be more Agile and implement technical SEO recommendations that add value.
Google is constantly evolving and a webmaster’s ability to react to changes is key to any successful SEO campaign. However, what happens when you can’t get technical SEO recommendations over the line? This session will focus on how you can be more Agile and implement technical SEO recommendations that add value.
The New Content SEO - Sydney SEO Conference 2023Amanda King
Amanda King of FLOQ's deck for the Sydney SEO conference run by Prosperity Media in April of 2023 on content, entity SEO and Google's history (or lack thereof) with keywords. We also go through natural language processing, what it is and how quickly Google goes from queries to entities based on their patent application history. And of course, no good conference session would go without actionable suggestions, which you can find at the end of the deck.
For another angle on content and strategy and how to approach them, read more at https://floq.co/seo-strategy/tactics-strategy/
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Google search vs Solr search for Enterprise search
1. Presented by
Veera Shekar G
Google Search VS Advanced Search (Enterprise
Search implemtation)
8/6/2015
11/05/2015
2. • A Normal Search engine processes.
• You will understand how search Engine Works.
• I am beginner at this subject.
• 5 Top requirements for Effective Enterprise search implementation.
• Problem with implementations.
Introduction
8/6/2015
11/05/2015
3. • Topic 1: How Search engine works.
▫ Will see architecture and component details.
• Topic 2: Google Search.
▫ Phases of implementation. Indexing architecture.
• Topic 3: Top 5 requirements for implementing Enterprise search.
▫ Options available for implementations.
Session Outline
8/6/2015
11/05/2015
4. • A Normal Search Engine Architecture.
• Architecture of a search engine factors determined .
• Indexing Process.
Topic 1: Objectives
8/6/2015
11/05/2015
5. • Architecture of a search engine can be viewed
as 2 Layered
Topic 1: Content – Normal Search engine Architecture
8/6/2015
11/05/2015
6. • Architecture of a search engine determined by 2
requirements –
effectiveness (quality of results)
efficiency (response time and throughput)
Topic 1: Content - Factors
8/6/2015
11/05/2015
7. • Text acquisition –identifies and stores documents for indexing.
• Text transformation –transforms documents into index terms or features
• Index creation –
takes index terms and creates data structures (indexes) to support fast searching
Topic 1: Content
8/6/2015
11/05/2015
8. • Search engine will have two main processes Indexing process and
Querying Process.
• Questions?
Topic 1: Wrap-up
8/6/2015
11/05/2015
9. • High Level Architecture of Google search.
• Web Crawlers.
• Technologies Used.
Topic 2: Google Search
8/6/201511/05/2015
11. • A web crawler is a program that, given one or more seed URLs,
downloads the web pages associated with these URLs, extracts any
hyperlinks contained in them.
• Recursively continues to download the web pages identified by these
hyperlinks. Web crawlers are an important component of web search
engines, where they are used to collect the corpus of web pages
indexed by the search engine.
Topic 2: Content - Web Crawlers
8/6/201511/05/2015
12. • Google visualizes their infrastructure as a three layer stack:
• Products: search, advertising, email, maps, video, chat, blogger
• Distributed Systems Infrastructure: GFS, MapReduce, and BigTable.
• Computing Platforms: a bunch of machines in a bunch of different data
centers
• Make sure easy for folks in the company to deploy at a low cost.
• Look at price performance data on a per application basis. Spend more
money on hardware to not lose log data, but spend less on other types
of data. Having said that, they don't lose data.
Topic 2: Content – Technologies Stack
8/6/201511/05/2015
14. • Top 5 requirements for implementing Enterprise search.
• Options available at each requirement.
Topic 3: Objectives
8/6/201511/05/2015
15. • Diverse Content: Ability to crawl, index and search diverse content repository.
The Web, Microsoft SQL database and SharePoint content management systems.
• Secured Search: Ability to crawl secured content and make it accessible to only authorized people
and/or groups.
Single sign-on, forms-based authentication.
• User Interface: Ability to provide various user interface (UI) components to serve end users with
precise results.
Guided navigation, related search terms, related articles and best bets.
AutoSuggest with terms combined from real-time search and custom (user configurable) terms
in data stores
• Desktop Search: Ability to integrate with content stored in the desktop.
• Social Search: Ability to find other people, ratings and expertise within the organization.
Topic 3: Content - Top 5 requirements for implementing
Enterprise search
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16. • Google Web crawler for crawling and indexing Web content (GOOTB).
• Google DB connector for crawling and indexing Microsoft SQL database (GOOTB).
• Google SharePoint connector for crawling and indexing SharePoint content (GOOTB).
• Google forms authentication for index time authorization and serve time authentication
(GOOTB).
• Google front-end configuration for:
> Faceted search, aka guided navigation (limited OOTB).
> Related search terms (GOOTB).
> Related articles (GOOTB).
> Best bets (GOOTB).
> Autosuggest (GOOTB and custom application).
• Google desktop search component integration (external Google component).
• Google results integration with internal rating system
Topic 3: Content – Google implementing requirements
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18. • Google Web Crawler.
• Disadvantage: As efficient and good as it sounds, one disadvantage of
Web crawler is Google’s inability to reveal the exact page that is
currently being processed.
• Alternative: The OS console monitor and/ or tracking log files are some
ways that could help track URL crawl status.
• At any point of time, a developer should be able to view the current URL
being crawled and issues faced (if any) with security. Almost all tools
provide this feature – such as Solr, FAST, Endeca and Autonomy.
Topic 3: Content – Web crawler
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19. • Database Connector.
• Disadvantage:
Google’s inability to allow end implementers to schedule DB crawl
Poor diagnostics for connector/XML-fed content.
Google’s way of removing content from index is quite primitive and time-consuming.
• Alternative: Alternative: Compared to GSA, It found Apache Solr is a better
option for indexing the database via data import handler.
• Solr provides an effective way to remove content from the index, either via
the admin console or via XML import (/update with delete option).
Topic 3: Content – Database Connector
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20. • Google provides connectors to very few CMS systems out of the box.
• Disadvantage:
Even if Google is executing a bulk late binding, performance issues
at query time are inevitable when the document volume is high.
• Alternative: One alternate is to consider the site/page/document level
security as an additional metadata, develop an application that would
post-filter the results based on end-user security attributes. This is again
a primitive method and has its own disadvantages in terms of query
time latency.
Topic 3: Content – SharePoint Connector (for Document
Management system)
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21. • At query time, Google uses the query time configuration to make an HEAD
request that would allow the logged-in user (within a specific domain) to view
only the content that he is authorized to view
.
• Disadvantage:
This late binding security model has performance degradation is
inevitable with higher QPS and/or higher results count.
• Alternative: There are tools that support an early binding security model that
allows the search engine to cache the user security groups along with the
content.
Topic 3: Content – Forms Authentication
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22. • One disadvantage with Apache Solr is that it does not handle secured
content. The only way to serve secured content is to store the security
tags/groups as one of the metadata and implement a field (or
metadata) constrained search.
• That is were ACL’s come into picture.
Note
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23. • GSA provides an open source component called “search-as-you-type” which
allows end implementers to fetch real-time results from the appliance.
• Disadvantage:
Onebox modules are designed to respond within one second. This could
result in no results from TermFederator if there is any delay at the
database.
• Alternative: “TermComponent” in Apache Solr is an effective autosuggest tool.
Terms stored in any local text file can be made available to Solr at startup. A
separate component designed to merge alphabetically.
Topic 3: Content – Auto Suggest
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24. • Best Bets — aka Keymatches, aka AdWords.
• Related search terms same as synonyms.
• Faceted search, aka Guided Navigation: GSA does not support faceted search.
But this feature can be achieved via metadata constrained search at query time,
similar to how it is implemented in Solr.
• Disadvantage: Facet count in GSA is not available OOTB.
• Alternative: Faceted search is one of Apache Solr’s strongest features and is
implemented within many e-commerce Website
And (Oracle) Endeca and (HP) Autonomy maintain content hierarchy for guided
navigation.
Topic 3: Content – User Interface
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25. • InfoValuator component captures end-user rating and saves a
combination of user identity, content URI and value rating in the backend
data store.
Topic 3: Content – InfoValuator
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26. • There is no one search engine that fulfills all enterprise search
requirements. HP Autonomy claims this lofty perch but it comes with a
huge cost overhead, with the base cost crossing half a million dollars.
• Google is not the right fit for many requirements that we have seen so
far. Custom search application development is inevitable and if well
planned, we can basically use any tool in the market to implement
enterprise search as a full-fledged application.
Summary of Session
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Editor's Notes
How presentation will benefit audience: Adult learners are more interested in a subject if they know how or why it is important to them.
Presenter’s level of expertise in the subject: Briefly state your credentials in this area, or explain why participants should listen to you.
Lesson descriptions should be brief.
Example objectives
At the end of this lesson, you will be able to:
Save files to the team Web server.
Move files to different locations on the team Web server.
Share files on the team Web server.